Data Scientist 3 at Lam Research

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

20 Mar, 26

Salary

0.0

Posted On

20 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, AI/ML, MLOPS, Cloud Computing, Python, R, Statistical Modelling, Project Management, Agile Methodologies, Stakeholder Management, Problem Solving, Decision Making, Communication, Leadership, Big Data Technologies, Machine Learning

Industry

Semiconductor Manufacturing

Description

The group you’ll be a part of LIDAS (Lam India Data Analytics and Sciences) team is responsible to provide best-in-class analytics solutions that help improve business decisions in Global Operations and other business sub-functions across Lam. This Organization, a “Center of Excellence” (CoE), consists of a high-performing team of experts who collaborate cross-functionally and provide analytics solutions to various business functions to suit their business needs. This team strives to improve the productivity & efficiency of business processes through business analytics, data science & automation projects. The resulting projects help accelerate businesses/stakeholders in decision-making by providing data insights. The team continuously develops the required technical skills and business acumen to help solve complex business problems & Use Cases in the semiconductor, manufacturing, and supply chain domains for the company. Overview We are seeking a seasoned and visionary AI/ML Solution Architect to lead the design and implementation of our AI/ML infrastructure, ensuring the creation of robust, scalable, and innovative solutions. The ideal candidate will combine deep technical expertise in data science and analytics with a strategic mindset to drive the development of cutting-edge AI/ML architectures. This position also involves deep understanding in implementing ML Solutions into Production with MLOPS and ML Failsafe mechanism. Responsibilities Responsibilities: Design and implement end-to-end AI/ML architectures that align with business goals and scalability requirements. Provide strategic direction for the integration of advanced analytics, machine learning, and AI technologies. Select and evaluate data science tools, frameworks, and platforms to build a cohesive and efficient data science ecosystem. Experience in delivery ML solution in Cloud environment ( Azure) . Hands On with the ML Model development and derive the right solutions for complex problem Stay abreast of emerging technologies to ensure the continuous evolution of our data science capabilities. Work closely with data scientists, engineers, and business stakeholders to understand requirements and translate them into architectural solutions. Foster a collaborative environment that encourages cross-functional innovation. Establish monitoring mechanisms to track model performance and address issues proactively. Responsible for delivering quick POCs and bringing data insights by using different complex data, and multiple data sources. Responsible to Provide technical leadership for developing end-to-end solutions and offering hands-on guidance. Mandatory Skills Mandatory Skills needed to perform the job: Proven experience as a Data Science Architect, with a track record of successfully implementing complex AI/ML/DL enterprise-wide solutions. Strong proficiency in programming languages (e.g., Python, R) and familiarity with data science libraries and frameworks. Expertise in machine learning, statistical modelling. Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Hadoop, Spark). Well versed with MLOPS and MLFAILSAFE concepts. Hands-on working experience in project management and agile methodologies. Tools like MS Project, etc. Good skills in managing Stakeholders’ (internal and external) Expectations. Strategic thinker with the ability to align technical solutions with business objectives. Excellent communication and leadership skills. Strong problem-solving and decision-making abilities. Ability to thrive in a dynamic and collaborative work environment. Preferred qualifications Years of Experience: Minimum 8 to 12 years Job Experience: Expertise in developing Data Science enterprise-wide sustainable solution, BI Applications, and Analytics. Design & Architecture. Educational: Master's or Ph.D. in Computer Science, Data Science, or a related field. Our commitment We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results. Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees. Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories – On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.

Responsibilities

Design and implement end-to-end AI/ML architectures that align with business goals. Collaborate with data scientists and engineers to translate requirements into architectural solutions.